The Centers for Disease Control and Prevention (CDC), in collaboration with Georgia Tech, is using data from social media platforms, like Reddit or Twitter, to strengthen the AI suicide predictions accuracy.

Since current statistics is often delayed by years, the first step is to provide real-time data for understanding “the real picture of what is going on in the world in terms of people’s mental health experiences”, shared Munmun de Choudhury, a professor at Georgia Tech, who works on the project for CDC.

To reduce the lag time, researchers are combining data from various types of sources: previous suicide rates, data from suicide helplines, hospitals, social media platforms like Twitter, Reddit, Google Trends, Youtube Search etc. – while AI is determining “signals” about future suicide rates, shared Choudhury:

“You train a machine-learning model using data and then you apply that model on an unseen data set to see how well it is doing. The project was: How can we intelligently harness signals from these different real-time sources in order to offset this one- to two-year lag?”

However the project is still in an early stage, it has shown the error rate of less than 1%, according to Choudhury. Now the professor wants to go further to help the preventing measures, using AI to alarm on potential suicide attempts.

As Future Time previously, Australian researchers from Monash University, in collaboration with national addiction treatment centre Turning Point and Eastern Health Foundations, also strive to improve suicide prevention using AI technologies.

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